Driver inattention is considered to be the most prevalent cause of vehicle collisions. One study attributes 45% of all crashes and near crashes in an urban environment to driver inattention. (See Dingus et al., “The impact of driver inattention on near-crash/crash risk: An analysis using the 100-car naturalistic driving study data”, National Highway Traffic Safety Administration (NHTSA) publication, 2006.). Another study estimated in 2003 that inattention caused between 25% and 30% of the police reported traffic crashes in the United States (See Hunter et al., “Driver inattention, driver distraction and traffic crashes”, ITE Journal, 2003), which amounts to approximately 1.2 million crashes per year. Per the NHTSA's “Distracted Driving 2011” study (National Center for Statistics and Analysis, 2013), drivers not paying attention caused 387 000 injuries and 3000 deaths per year in the U.S. in 2011, and a similar study found that between 2005 and 2007, driver inattention was responsible for 32% of all the roads fatalities in Western Australia. (See Government of West Australia. Driver distraction—fact sheet. Road Safety Commission publication, 2014.) Clearly, there is a significant potential for reducing crashes, injuries and fatalities by addressing the issue of driver attention.
Driver Monitoring Systems (DMS) observe the behavior of a vehicle's driver and extract driver information, such as drowsiness, point of focus or “gaze position” (e.g., dashboard, rear view mirror, instrument cluster, etc.), or whether the driver has fallen asleep. This information is provided to a driver monitoring application that may take some sort of action, e.g., warning or waking the driver, or adjusting timing parameters in automated driver assistance system. The main purpose of driver monitoring applications is to avoid accidents due to driver inattention, but they may also be used for comfort functions, such as head-up display adjustment, etc. Essential to a driver monitoring application is an estimated position and velocity of the driver's head, especially for computing the driver's gaze position and gaze direction. It is not sufficient to estimate the position in two dimensions only. The gaze direction and gaze position are dependent on the three dimensional position of the head. Errors made in the head position estimate propagate to errors in the gaze position and gaze direction. A camera-only approach, with various techniques, may provide an estimate of the z-position (i.e., roughly normal to the driver's face), but may be expensive (requiring use of multiple cameras), and/or may provide an inherently low accuracy of the z position estimate (by using a single camera together with, e.g., an inter-pupil distance calibration procedure).
Therefore, a separate means to accurately and cheaply determine the three dimensional position and velocity is of great value for driver monitoring applications.